The impetus of 3D printing technology in recent years is significant. Many printer manufacturers exist and new companies seem to appear overnight. Despite this wave of new developments, in many (if not most) cases, the reliability of the technology is limited, and printed, or additive manufactured (“AM”), parts suffer from defects that lead to subpar strength and fatigue life when compared to parts manufactured with conventional technologies. This negative aspect limits severely the spread of the technology. Computer simulations are sought to provide insight into the process so that progress in raising the quality of AM parts can be achieved.
Many physics-related aspects of the additive manufacturing process are similar to some of the conventional manufacturing technologies, such as casting and welding. Material is added in a hot and fluid state and then it cools down. In additive manufacturing, the material is added incrementally in a molten state or is brought to a molten state by a moving heat source (e.g., laser) after which cooling occurs on a continuously evolving surface. The additional challenges with AM, particularly with metal fabrication, have to do with the vast disparity in time and length scales that one has to deal with during manufacturing: very localized and rapidly evolving physics in the “action” zone while the manufacturing process for the whole part takes hours or perhaps days.
The efforts to develop numerical techniques to simulate certain aspects of an additive manufacturing process are numerous and span several communities of scientists and engineers from academics to applied research commercial entities. The difficulties to capture/predict via computer simulations such processes are many, including: (1) vastly different time scales of the melting/solidification physics (milliseconds) and the overall manufacturing time of a typical part (hours of printing on the machine); (2) wide range of scale lengths, from microns associated with melt pools to hundreds of millimeters necessary to model a typical part; (3) rapidly evolving high temperature gradients around the “action” zone, which leads to highly anisotropic material final properties (before eventual heat treatment); (4) assuming that adequate models are employed, very large simulation times are typically necessary to model such processes in order to capture all of the above.
Developing novel numerical schemes would be necessary to cope with all these challenges. The following are examples of existing technologies, each of which do not solve the difficulties described above:
3DSIM is a company that claims it develops efficient numerical simulation technology based on finite elements. 3DSIM's method appears to take advantage of adaptive mesh refinement/coarsening techniques while leveraging advanced metal modeling constitutive behavior. See www.3dsim.com and I. Gibson, D. Rosen, B. Stucker, Additive manufacturing technologies: rapid prototyping to direct digital manufacturing, Springer, N.Y., 2009. The technology is intended for laser melting/sintering AM applications and employs an automated mesh refinement technique in the “action” zone (e.g., current laser location). However, it does not leverage actual laser path information and recoater/spreader bar throughout the part. Consequently, the overall cooling by convection and radiation for the whole part loses accuracy/predictiveness as a result. Moreover, the automated refinement/coarsening of the mesh has negative implications on the overall computational performance when analyses are run in parallel on multiple CPUs (especially on a large number of CPUs).
PANCOMPUTING is another example of a company that leverages finite element-based solutions. PANCOMPUTING's method also incorporates adaptive mesh refinement techniques and is able to make predictions of undesired distortions during the printing process. See www.pancomputing.com and P. Michaleris, “Modeling metal deposition in heat transfer analyses of additive manufacturing processes In situ monitoring.” Finite Elements in Analysis and Design (2014): 51-60. The technology is similar to 3DSIM and faces similar limitations.
The United State National Labs have also been investing on the topic with Los Alamos and Lawrence Livermore leading the effort. At Los Alamos, long time existing casting simulation software is currently being adapted/re-purposed to study numerically AM processes (see Truchas casting software available at www.lanl.gov). At Lawrence Livermore, comprehensive simulation technology is being developed to address at a micro-scale the complex physics of phase transitions from powder, to liquid, to solid and attempting to predict residual stresses for very small parts. See N. E. Hodge, R. M. Ferencz, J. M. Solberg, “Implementation of a thermomechanical model for the simulation of selective laser melting” Comput Mech (2014) 54:33-51). The US National labs do not seem to focus on accurate predictions for part-level simulations. Instead, they seem to be spending much effort in understanding the basic behavior on very small-scale models without paying enough attention on overall behavior as far as realistic parts are concerned.
Academics researching the topic are too numerous to list here in a comprehensive fashion. Many leverage old existing models developed originally for welding or casting, such as described in J. B. Leblond, “Mathematical Modeling of Transformation Plasticity in Steels,” International Journal of plasticity, Vol 5, 573-591, 1989. More recent works (such as in Xipeng Tan, Yihong Kok, etc. “An experimental and simulation study on build thickness dependent microstructure for electron beam melted Tie6Ale4V, Journal of Alloys and Compounds 646 (2015) 303-309) focus on more or less sophisticated material constitutive behavior models that are quite valuable and practical. Academics of all sorts, similar to the National Labs, also do not have a focus on part-level simulations for scalable predictive solutions. When part-level presentations are included, the geometry associated with the shape is severely simplified to accommodate for the lack of technology in dealing with realistic parts.
Numerical modeling of heat treatment related applications has a significant relevance in modeling, in the case of metals, of metallurgical transformation throughout the part being modeled. See www.dante-solutions.com and B. Lynn Ferguson and Zhichao Li, “Using Simulation for Heat Treat Process Design: Matching the Quenching Process”, ICTPMCS-2010, 31 May-2 Jun. 2010, Shanghai, China. Heat treatment software packages, while very relevant for AM process simulation from a variety of perspectives, suffer from a severe limitation: they lack the ability of simulating local thermal aspects (such as laser heating) and managing evolving surfaces of an additive manufacturing process
Thus, despite the numerous prior efforts for developing the various numerical modeling technologies, there is still a number of rather significant limitations associated with these developments.